High-fidelity quantum-state preparation is a central task in quantum information science. In practice, it is commonly guided either by full quantum state tomography, which becomes prohibitively resource-intensive as system size grows, or by empirically chosen measurement settings that lack principled optimality. Here, we show that quantum state verification (QSV) can be elevated from a purely diagnostic tool to a prescriptive framework for quantum-state preparation, directly specifying experimentally optimal measurements and quantitative fidelity indicators without full state reconstruction. We experimentally realize this prescriptive paradigm using a three-qubit nonstabilizer $W$ state and a modified homogeneous QSV protocol. The verification measurements not only certify the prepared state with high confidence but also serve as a tomography-free indicator that systematically informs the preparation procedure. Using only nine measurement settings and ${10}^4$ samples, we achieve high-fidelity state preparation consistent with full tomography that requires orders of magnitude more resources. Beyond the present implementation, the prescriptive structure of QSV is naturally compatible with closed-loop feedback control, outlining a pathway toward genuine real-time quantum-state preparation in future low-latency platforms.

Realizing deterministic and bright single-photon sources with minimal two-photon probability at room temperature is essential for quantum communication, computation, and sensing. Solid-state quantum emitters, particularly nitrogen-vacancy (N-$V$) centers in diamond, are prime candidates for single-photon emission and spin addressability but suffer from limited photon extraction efficiency and higher two-photon probability. Here, we demonstrate efficient coupling of single N-$V$ centers in diamond nanowaveguides to guided optical modes, enabling enhanced single-photon outcoupling with low two-photon probability. By optimizing excitation and collection geometry, we achieve a single-photon count rate of approximately $2\text{Mcps}$ along with a low two-photon probability of $g^{(2)}(0)=0.014\pm 0.004$. The nanowaveguide architecture overcomes alignment and bandwidth constraints of resonant cavities, providing a scalable, fabrication-compatible route for bright single-photon sources.

The laser-ranging interferometer (LRI) serves as a core payload for space-based gravitational-wave missions, as well as for gravity recovery missions. In this work, a ground-based simulator reproducing a three-spacecraft formation with six interferometric links is developed to emulate a subset of the on-orbit configuration of space-based missions. The formation is realized on air-bearing platforms forming a 10 m equilateral triangle, thereby providing a dynamic experimental environment. Each spacecraft (S/C) carries a complete set of in-house developed interferometric payloads, including an NPRO laser, a laser frequency stabilization system, two optical benches, and an integrated field programmable gate array (FPGA)-based electronics unit. The FPGA implements key functions, including weak-light phase locking, phasemeter, and differential wavefront sensing (DWS). In experiments, all six laser links are successfully established and operated simultaneously, effectively reproducing the configuration of an on-orbit S/C interferometer. At 4 mHz, the laser frequency stability is better than $80\mathrm{Hz}/\sqrt{\mathrm{Hz}}$, the weak-light phase-locking control noise is below $2\times {10}^{-4}\mathrm{rad}/\sqrt{\mathrm{Hz}}$, and the pointing stability is better than $4\mathrm{\mu }\mathrm{rad}/\sqrt{\mathrm{Hz}}$. The optical bench and the air-bearing platform exhibit displacement noise at the micrometer and sub-millimeter levels, respectively. This work provides a systematic and multi-perspective validation of S/C formation interferometry for space-based gravitational-wave detection, laying an important experimental foundation for future space missions.

The semiconductor chip manufacturing process is complex and lengthy, and potential errors can arise at every stage. Each wafer contains numerous chips, and wafer bin maps can be generated after chip testing. By analyzing the defect patterns on these wafer bin maps, the manufacturing steps at which errors occur can be inferred. In this work, we improve the quantum Bayesian inference algorithm and apply the proposed algorithm to accelerate the identification of error patterns on wafer bin maps, thereby assisting in chip yield analysis. We show the algorithm for error identification and detail the implementation of the improved quantum Bayesian inference. Our results demonstrate the speed advantage of quantum computation over classical algorithms for a real-world problem, highlighting the practical significance of quantum computation for many problems based on Bayesian inference.

We present a countermeasure against the detector-blinding attack (DBA) utilizing statistical analysis of error and double-click events accumulated during a quantum key distribution session under randomized modulation of single-photon avalanche diode (SPAD) detection probabilities via gate voltage manipulation. Building upon prior work demonstrating the ineffectiveness of this countermeasure against continuous-wave (cw) DBA, we extend the analysis to evaluate its performance against pulsed DBA. Our findings reveal an approximately 13 dB increase in the trigger pulse energies difference between default and reduced gate voltage applied under pulsed DBA conditions compared with cw DBA. This heightened difference enables a re-evaluation of the feasibility of utilizing SPAD detection probability variations as a countermeasure and makes it possible to estimate the fraction of bits compromised by an adversary during pulsed DBA.

Optically active spin qubits have emerged as powerful quantum sensors capable of nanoscale magnetometry; yet conventional coherent sensing approaches are ultimately limited by the coherence time of the sensor, typically precluding detection in the sub-MHz regime. We present a broadly applicable fluorescence-encoding method that circumvents coherence-time constraints by transducing time-varying magnetic fields directly into modulated fluorescence signals. Using nitrogen-vacancy centers in diamond as a model system, we demonstrate shot-noise-limited sensitivity for ac magnetic fields spanning near-dc to MHz frequencies, with detection bandwidth tunable via optical excitation power. The technique captures complete spectral information in a single measurement, eliminating the need for point-by-point frequency scanning, and allows phase-sensitive multifrequency detection. This approach transforms quantum sensors into atomic-scale spectrum analyzers, with immediate applications for low-frequency rf communication, zero-field nuclear magnetic resonance, and bioelectronic sensing. Our approach is broadly applicable to the expanding class of optically active spin qubits, including molecular systems and fluorescent proteins, opening new sensing regimes previously inaccessible to coherent techniques.

Quantum transport in atomistic devices is governed by both localized quantum coupling and long-range Coulomb interactions. However, existing deep learning models for device simulation struggle to capture these inherently nonlocal effects. To address this challenge, we propose the Position-Aware Global Attention Network (PGA-Net), a Transformer-based architecture for quantum transport simulation. PGA-Net introduces a multiscale physical field learning framework that integrates local physical encoding with global attention decoding, along with a trainable two-dimensional (2D) positional encoding to enhance spatial structure awareness. By learning an end-to-end mapping from device inputs to the atomistic electrostatic potential outputs, PGA-Net achieves up to a $10\times$ simulation speedup while maintaining consistency with the nonequilibrium Green’s function method. On a dataset of 6015 2D atomistic MOSFET samples, PGA-Net attains a mean absolute error below 0.02 V for potential prediction. Moreover, the learned physical representations can be further used to recover other key transport-related quantities, such as the charge density and the local density of states. Overall, this work provides an efficient route for atomic-scale device simulation under similar physical assumptions and boundary conditions and offers insights into extending physics-aware global attention mechanisms to broader device-level modeling.

Numerical calculus algorithms, which estimate derivatives and integrals from data series acquired either via measurements or by sampling functions, are essential in scientific computing. To date, few quantum algorithms have been developed to perform calculus operations based on closed-form functional inputs; yet, in many practical applications, field variables are numerically described via a series of samples rather than closed-form expressions. This paper presents the theoretical development and the gate-level circuit implementation of quantum algorithms for numerical differentiation and, up to addition of a constant, indefinite integration. The methodology relies on a spectral approach that leverages the computational efficiency of the quantum Fourier transform and the parallel computing capability afforded by quantum superposition to evaluate outputs at all domain points simultaneously. The differentiation approach is also extended to enable gradient estimation, and postprocessing procedures are presented to recover sign information. The primary outputs of the proposed algorithms are quantum state vectors directly proportional to the numerical derivative or integral of the given data; therefore, the correctly signed results are made available to proceeding quantum computations. This result lays the foundation for the proposed algorithms to serve as core subroutines in applied quantum computing operations, such as image processing, data analysis, and machine learning.

Microrheology involves the study of matter’s rheological properties at the microscale and has a wide application in biology, chemistry, and other fields. Exploring the microrheology of intracellular fluids is critical for understanding cell dynamics and related biological processes, and providing insights into cell physiology. Here, we present a label-free, noninvasive microrheology platform that simultaneously integrates holographic optical tweezers for 3D manipulation with double-helix point spread function microscopy for 3D localization. Without using externally labeled particles, an arbitrary endogenous particle within pyroptotic cell can be captured by holographic optical tweezer and moved to desired area in 3D space. Double-helix point spread function microscopy can enhance the imaging contrast of trapped particle and precisely determine its 3D position without prior knowledge of particle size or repeated calibration. The relative viscosity of intracellular fluid is then derived from the trajectory of probe. The label-free microrheology technology was applied to pyroptosis cells for the first time, revealing a relative viscosity gradient from the cell membrane to the nucleus region. This noninvasive approach can avoid external influences on the normal dynamics of cells and provide an in situ platform for the study of intracellular fluid heterogeneity, which will help elucidate the mechanisms of cell death and inflammation.

Zinc oxide (ZnO) has garnered much attention as a promising material for quantum devices due to its unique characteristics. To utilize the potential of ZnO for quantum devices, the development of fundamental technological elements such as high-speed readout and charge sensing capabilities has become essential. In this study, we address these challenges by demonstrating radio-frequency (rf) reflectometry and charge sensing in ZnO quantum dots, thus advancing the potential for qubit applications. A device is fabricated on a high-quality ZnO heterostructure, featuring gate-defined target and sensor quantum dots. The sensor dot, integrated into an rf resonator circuit, enables the detection of single-electron charges in the target dots. Using this setup, we observe the rf-detected charge stability diagram indicating the formation of few-electron double quantum dots and provide the first benchmark of the bandwidth, sensitivity, and readout fidelity of rf reflectometry.

We study ballistic transport in bilayer graphene junctions and show how electrostatic gating, interlayer bias, and homogeneous strain provide complementary control over electron transmission. In the absence of strain, transport is governed by symmetry constraints that suppress transmission at specific incidence angles despite the availability of states. An interlayer bias lifts this suppression through mode mixing and opens a tunable transport gap. Within a full four-band description, we identify a distinct conductance threshold that marks the onset of propagation of the upper band inside the barrier. This produces a clear change in the slope of the conductance and serves as an experimentally accessible transport fingerprint of the multiband structure and interlayer coupling. Homogeneous in-plane strain acts as a geometric control mechanism. By reshaping the band structure in momentum space, it redistributes the angular transmission window and suppresses conductance without introducing disorder. Notably, strain preserves the underlying symmetry-based decoupling responsible for transmission suppression while shifting its condition away from normal incidence. These results provide a unified framework for interpreting angle-resolved transport in bilayer graphene and establish multiband ballistic transport as a practical probe of band-structure geometry.

We demonstrate a dissipative protocol for ground-state preparation of a quantum spin chain on a trapped-ion quantum computer. As a first step, we derive a Kraus representation of a dissipation channel for the protocol recently proposed by Ding et al. [Single-ancilla ground state preparation via lindbladians, Phys. Rev. Res. 6, 033147 (2024)] that still holds for arbitrary temporal discretization steps, extending the analysis beyond the Lindblad dynamics regime. The protocol guarantees that the fidelity with the ground state monotonically increases (or remains unchanged) under repeated applications of the channel to an arbitrary initial state, provided that the ground state is the unique steady state of the dissipation channel. Using this framework, we implement dissipative ground-state preparation of a transverse-field Ising chain for up to 19 spins on the trapped-ion quantum computer Reimei provided by Quantinuum. Despite the presence of hardware noise, the dynamics consistently converges to a low-energy state far away from the maximally mixed state even when the corresponding quantum circuits contain as many as 4110 entangling gates, demonstrating the intrinsic robustness of the protocol. By applying zero-noise extrapolation, the resulting energy expectation values are systematically improved to agree with noiseless simulations within statistical uncertainties.

Two-dimensional (2D) van der Waals (vdW) ferromagnet ${\text{Fe}}_5{\text{GeTe}}_2$ (F5GeT2) is a promising candidate for spintronic applications due to its intrinsic near-room-temperature ferromagnetism, magnetic anisotropy, excellent tunability, and emergent topological magnetic textures. However, the delicate ferromagnetic order and moderate magnetic anisotropy hinder its practical implementation in next-generation spin-based devices. Doping with specific elements has been demonstrated to be an effective strategy for enhancing ferromagnetism and elevating the Curie temperature ($T_C$) in such systems. In this work, we synthesized lightly Ni-doped $({\text{Fe}}_{5-x}{\text{Ni}}_x{)}_5{\text{GeTe}}_2({\text{Ni}}_x\text{−}\mathrm{F}5\text{GeT}2)$ single crystals and conducted a comprehensive investigation into their magnetic properties. We found that even a small amount of Ni-doping can significantly elevate $T_C$ and enhance the easy in-plane anisotropy (EPA) compared with pristine F5GeT2. By employing the modified Arrott plot (MAP) method and critical isotherm (CI) analysis, the critical exponents for two distinct magnetic field orientations are obtained. For ${\text{Ni}}_{0.05}\text{−}\mathrm{F}5\text{GeT}2$, we determine $\beta =0.385(7)$, $\gamma =1.303(4)$, and $\delta =4.696(5)$ for $H//ab$, and $\beta =0.359(1)$, $\gamma =1.195(7)$, and $\delta =4.455(1)$ for $H//c$. For ${\text{Ni}}_{0.1}\text{−}\mathrm{F}5\text{GeT}2)$, we find $\beta =0.354(9)$, $\gamma =1.342(5)$, and $\delta =4.764(6)$ for $H//ab$, and $\beta =0.368(2)$, $\gamma =1.242(1)$, and $\delta =4.561(1)$ for $H//c$. These derived exponents exhibit excellent self-consistency and adhere to the Widom scaling relation. However, the critical exponents do not conform to any single theoretical universality class, which indicates the presence of anisotropic magnetic exchanges induced by the Ni-doping. The magnetic interactions of ${\text{Ni}}_{0.05}\text{−}\mathrm{F}5\text{GeT}2$ and ${\text{Ni}}_{0.1}\text{−}\mathrm{F}5\text{GeT}2$ fall between the short-range and long-range limits, suggesting that low-concentration Ni-doping modulates the spin decay distances of the system. Our findings establish a pathway for tailoring the magnetic properties of 2D-vdW ferromagnets through doping engineering, expanding the prospects for developing high-performance room-temperature spintronic devices.

Magnetic skyrmions are topologically distinct spin textures that hold significant potential for applications in information storage and processing. In this study, we investigate the transformation of various dipolar-stabilized spin textures present in amorphous ferrimagnetic Gd/Fe multilayers under the influence of in-plane magnetic field components. Using Lorentz transmission electron microscopy, we observe the nucleation of three different types of magnetic spin objects in the presence of an out-of-plane magnetic field. By tilting the sample up to 18°, the relative contribution of the in-plane field is varied, enabling controlled transformations between topologically trivial and topologically protected types of spin objects. We find that the in-plane field component plays a critical role in determining the topological nature of the stabilized spin objects. Additionally, local variations in spin texture appearance are observed and linked to intrinsic membrane wrinkling, which induces a tilted anisotropy axis and effective in-plane fields. These findings, supported by micromagnetic simulations, highlight the tunability of spin objects through controlled field application, paving the way for alternative strategies in spintronic device engineering.

In this study, we report a robust cryptographic scheme operating over noisy channels, enabled by a nonlinear detection architecture that intrinsically mitigates channel-induced phase aberrations. Difference-frequency generation (DFG) in a nonlinear crystal is employed to automatically compensate channel-induced phase aberrations, providing intrinsic noise mitigation. Spatial modes in the orbital angular momentum basis are used as high-dimensional information carriers, providing enhanced capacity and improved security. As a classical proof-of-principle, our results demonstrate that the DFG correction mechanism reliably restores the spatial mode transfer matrix to near-ideal fidelity across a broad range of aberration types and strengths, recovering projected secret key rates and mutual information metrics consistent with a secure high-dimensional channel. These findings establish nonlinear wave mixing as a viable tool for noise-resilient, high-dimensional communication, with a clear pathway toward quantum implementation using single-photon sources and detectors.

Coherent ferrons, the quanta of polarization waves, can potentially be hybridized with many other quasiparticles for achieving novel control modalities in quantum communication, computing, and sensing. Here, we theoretically demonstrate a new hybridized state resulting from the strong coupling between fundamental-mode (wavenumber is zero) coherent ferrons and cavity bulk acoustic phonons. Using a van der Waals ferroelectric ${\text{CuInP}}_2{\mathrm{S}}_6$ membrane as an example, we predict an ultrastrong ferron-phonon coupling at room temperature, where the coupling strength $g_c$ reaches over 10% of the resonant frequency ${\omega }_0$. We also predict an in situ bistable electric-field control of mode-specific ferron-phonon hybridization via ferroelectric switching. We further show that ${\text{CuInP}}_2{\mathrm{S}}_6$ allows for reaching the fundamentally intriguing but challenging deep-strong coupling regime (i.e., $g_c/{\omega }_0>1$) near the ferroelectric-to-paraelectric phase transition. Our findings establish the theoretical basis for exploiting coherent ferron as a new contender for a hybrid quantum system with strong and highly tunable coherent coupling.

The rapid development of machine learning and quantum computing has placed quantum machine learning (QML) at the forefront of research. However, existing QML algorithms based on quantum variational algorithms face challenges in trainability and noise robustness. To address these challenges, we introduce a gradient-free, noise-robust quantum reservoir computing algorithm that harnesses discrete time crystal dynamics as a reservoir. We characterize the memory, nonlinear, and information scrambling capacities of the quantum reservoir, revealing their correlation with dynamical phases and nonequilibrium phase transitions. For ten-class classification, both noisy simulations and experimental results on superconducting quantum processors match ideal simulations, demonstrating that accuracy increases with system size and confirming topological robustness against noise. Our work presents the first experimental demonstration of quantum reservoir computing for image classification based on digital quantum simulation. Besides, it also experimentally demonstrates the relationship between many-body nonequilibrium dynamical phase transitions and QML performance. These findings introduce noise-robust and efficient design principles for quantum reservoir computing and broader quantum machine learning algorithms in the NISQ era.

Processing steps, such as thermal oxidation, creation of p- and n-doped regions via ion implantation, and postoxidation and postimplantation annealing, are essential for successful and reliable fabrication of devices based on $4H$-SiC. These processing steps are known to introduce crystalline defects or even modifications within the SiC base material that can potentially compromise device operation and reliability. In this work, we systematically study the strain introduced in the $4H$-SiC crystal by SiC-specific manufacturing methods. The results show that tensile strain is present after ion implantation, thermal oxidation, and subsequent annealing processes. Interestingly, aluminum implanted samples show compressive strain near the surface in addition to the presence of an additional Raman signature, while nitrogen and phosphorus implanted samples experience tensile strain. Density functional theory calculations were performed to corroborate the experimental data and connect the type of strain to the microscopic impact that different dopants have on the SiC lattice. These results contribute to the understanding of processing-induced modifications within the crystal and show that Raman spectroscopy is a powerful tool to assess modifications to the $4H$-SiC crystal.